Difference between revisions of "Group 7"
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We found plot of ‘VAST Challenge 2017’ to be intriguing, to the likes of a detective story. The plot unfolds with a clear purpose of identifying the most plausible factors that lead to the decline of the endangered bird species Rose-crested Blue Pipit at the Boonsong Lekagul Nature Preserve. We aim to propose a hypothesis backed by the deductions from our analysis. The dataset covers a broad range of data types, from timestamp of vehicles that move through the preserve, to gaseous effluents data from nearby factories and imagery data of the flora and fauna in the Preserve. | We found plot of ‘VAST Challenge 2017’ to be intriguing, to the likes of a detective story. The plot unfolds with a clear purpose of identifying the most plausible factors that lead to the decline of the endangered bird species Rose-crested Blue Pipit at the Boonsong Lekagul Nature Preserve. We aim to propose a hypothesis backed by the deductions from our analysis. The dataset covers a broad range of data types, from timestamp of vehicles that move through the preserve, to gaseous effluents data from nearby factories and imagery data of the flora and fauna in the Preserve. | ||
This will challenge us to deal with different types of data set and strive to find correlations between such varied data. | This will challenge us to deal with different types of data set and strive to find correlations between such varied data. | ||
Revision as of 20:59, 16 June 2017
ISSS608 Visual Analytics and Applications
The Curious Case of Rose-Crested Blue Pipit
Motivation
We found plot of ‘VAST Challenge 2017’ to be intriguing, to the likes of a detective story. The plot unfolds with a clear purpose of identifying the most plausible factors that lead to the decline of the endangered bird species Rose-crested Blue Pipit at the Boonsong Lekagul Nature Preserve. We aim to propose a hypothesis backed by the deductions from our analysis. The dataset covers a broad range of data types, from timestamp of vehicles that move through the preserve, to gaseous effluents data from nearby factories and imagery data of the flora and fauna in the Preserve.
This will challenge us to deal with different types of data set and strive to find correlations between such varied data.
Dataset Overview
We have 4 kinds of data available for this challenge:
- Timestamp data from the movement of vehicles through the Preserve
- Gaseous effluents data from the 4 surrounding factories
- Imagery data of the flora and fauna/ maps, etc
- Newsletters of the Preserve which may provide additional information on the Preserve.
Proposed Timeline
